ETC5523: Covid19: Austria

Introduction

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. It began spreading in earnest in the early 2020’s and has led to a global crisis of never-seen before proportions. People are being forced to stay indoors to reduce risk of exposure and spread of the disease.

Austria, a country in the Europe has also had to endure this crisis.

This blog post is aimed at investigating a few key articles that became breaking news during the time and checking the veracity of their claims.

The First Article

The Second Article

Citations

Hersche, D. I. B., Kern, U.-P. D. W. V., Stuber- Berries, D. N., Rohrer, D. R., Trkola, D. A., & Weber, U.-P. D. K. (2020, October 12). BERICHT DER UNABHÄNGIGEN EXPERTENKOMMISSION MANAGEMENT COVID-19-PANDEMIE TIROL. Vienna; Consumer Protection Association (VSV). https://www.verbraucherschutzverein.eu/wp-content/uploads/2021/08/Expertenkommission-Bericht.pdf

Guardian News and Media. (2020, November 27). ‘A Christmas not like others’: Europe wrestles with FESTIVE Covid rules. The Guardian. Retrieved September 15, 2021, from https://www.theguardian.com/world/2020/nov/27/christmas-not-like-others-europe-wrestles-festive-covid-rules.

Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686

Garrett Grolemund, Hadley Wickham (2011). Dates and Times Made Easy with lubridate. Journal of Statistical Software, 40(3), 1-25. URL https://www.jstatsoft.org/v40/i03/.

Hao Zhu (2021). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.3.4. https://CRAN.R-project.org/package=kableExtra

Yihui Xie (2021). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.31.

Yihui Xie (2015) Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963

Yihui Xie (2014) knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595